{"id":37097,"date":"2026-07-15T23:21:00","date_gmt":"2026-07-15T21:21:00","guid":{"rendered":"http:\/\/stocks-future.com\/?guid=29716312ac0174f281289ebe5b29d404"},"modified":"2026-07-15T23:21:00","modified_gmt":"2026-07-15T21:21:00","slug":"grafana-labs-named-a-leader-in-2026-gartner-magic-quadrant-for-observability-platforms-and-positioned-furthest-in-completeness-of-vision","status":"publish","type":"post","link":"https:\/\/stocks-future.com\/?p=37097","title":{"rendered":"Grafana Labs Named a Leader in 2026 Gartner\u00ae Magic Quadrant\u2122 for Observability Platforms and Positioned Furthest in Completeness of Vision"},"content":{"rendered":"

\nNamed a Leader for the third consecutive year and placed furthest in vision for the second year in a row, the company has had a landmark year of innovation as observability becomes essential infrastructure for teams building and running AI at scale.<\/i><\/p><\/a><\/a><\/a><\/a>

NEW YORK--(BUSINESS WIRE)--Grafana Labs, the company behind the open observability cloud, today announced it has been named a Leader in the Gartner\u00ae Magic Quadrant\u2122 for Observability Platforms<\/a> for the third consecutive year, and positioned furthest on the Completeness of Vision axis for the second year running.<\/p>

\nWe believe this placement reflects where the market is headed: toward open, composable observability that helps teams in the AI era understand systems that are increasingly complex and agentic, and rapidly scaling thanks to AI-assisted engineering.<\/p>

\nA Platform Built for the AI Era<\/b><\/p>

\nAccording to Grafana Labs\u2019 2026 Observability Survey<\/a>, operational complexity and overhead are now the top observability challenge, even as adoption of managed observability continues to climb, with half of organizations now using managed observability in some form (up from 43% in 2025). Telemetry keeps growing, systems keep getting more distributed, and teams are tired of paying twice: once for data they do not need, and again in engineering time when something breaks, and nobody can see the full picture. What changed in the last year is the scale of that problem. AI has become production infrastructure with its own failure modes, cost curves, and accountability questions, while the people operating these systems still need to move faster than dashboards alone allow.<\/p>

\nObservability has to serve both sides of the AI shift. Teams need to observe AI, from LLMs and agents to inference pipelines and the applications wrapped around them. And they need observability that uses AI responsibly to shorten investigations, not replace judgment. That demand is showing up across energy, manufacturing, media, and retail, and increasingly among AI-native companies<\/a> running production AI workloads on Grafana Cloud.<\/p>

\nThat\u2019s why over the past year, Grafana Labs expanded Grafana Cloud<\/a> to help teams run complex systems, observe AI in production, and use AI to move faster on an open platform where observability spend scales with value, not volume.<\/p>